Case Study
ZARM
Platform behind ZARM, a free 90-minute AI investment diagnostic for established businesses, with cohort scheduling and organization-scoped lead workflows.
ZARM is an AI investment diagnostic from Zylo: a working session that shows mid-market businesses where AI will, and will not, pay back before they spend on the wrong bet. Teams map where time and money go, rank the three highest-value opportunities, and put a financial figure on each one.
I built the backend foundations behind the experience: structured lead automation, cohort and seat management, RBAC, governed artifacts, and repeatable workflows that keep every handoff clean from first application to the working session.
Role
Backend systems + workflow design
Focus
Governed lead pipelines and organization-aware workflow architecture.
Delivery
Operational CRM flows with cleaner product handoffs.
Key Features
- Application flow for a limited-seat, 90-minute diagnostic session
- Cohort scheduling with live seat availability (open, filling, waitlist)
- Organization-scoped lead, questionnaire, and workshop workflows
- Role-based access control and governed artifacts
- Case-study proof pages that quantify manual work, payback, and return
- Hand-off into a dedicated platform sign-up for each accepted business
What Makes It Interesting
ZARM sells a diagnosis rather than a tool, so the product has to feel precise: capped cohorts, accurate seat counts, and numbers that come from the client's own data. That put the weight on reliable workflow and permission design behind a very simple front door.